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- Wadensten, T., et al.
(författare)
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A Smartphone app For Self-Management of Urgency and Mixed Urinary Incontinence : a Randomized Controlled Trial
- 2019
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Ingår i: Neurourology and Urodynamics. - : John Wiley & Sons. - 0733-2467 .- 1520-6777. ; 38, s. S361-S363
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Hypothesis / aims of study: Urgency (UUI) and mixed (MUI) urinary incontinence are common clinical problems. They account for almost half of all cases of urinary incontinence (UI) in women [1], and have a potentially large impact on quality of life. Nonetheless, many women are reluctant to seek treatment, sometimes due to UI being a stigmatized condition. The recommended first-line treatment for UUI and MUI is pelvic floor muscle training (PFMT) and lifestyle advice [2], with bladder training as a valuable complement to the treatment. Previous studies have shown that a smartphone app was an effective form of self-management for women with stress urinary incontinence (SUI), both in terms of treatment efficacy [3] and cost-effectiveness. On-going studies show promising results of the app once it was made freely available for download, and a further study of the user experience of the app found that the app provided an appreciated and satisfactory experience. In this study, we aimed to evaluate whether a new smartphone app for the self-management of UUI and MUI in women was effective, in comparison to app-based information only. Study design, materials and methods: Between April 2017 and March 2018, women were consecutively recruited to this randomized controlled trial (RCT) via a screening questionnaire on the homepage of the research project. The trial has been Clinical Trials registered. The inclusion criteria were as follows: woman (gender self-stated and sex assigned at birth), ≥18 years, UUI or MUI with ≥2 leakages/week and ≥12 months of symptom duration. Pregnant women or women who used another PFMT app or anti-muscarinic drugs were not eligible to participate in the study. In order to identify and redirect cases that were better suited to receive usual care, an algorithm was developed by a team of professionals with both clinical and scientific experience from fields such as urogynecology, general practice, urology and incontinence care. The algorithm included questions on the person’s history of cancer in the pelvic region, diabetes, and neurological symptoms and diseases, as well as questions on certain alarm symptoms (e.g. painful urges, dysuria, haematuria, metrorrhagia, recurring urinary tract infections, bladder-emptying difficulties and pyelonephritis). The presence of any alarm symptom led to the respondent being classified as not eligible for the study and instead recommended to contact their usual medical care provider. Women who passed the screening questionnaire and submitted an email address received information about the study, and were asked to fill in an Informed Consent form, a two-day bladder diary and a baseline questionnaire which included the International Consultation on Incontinence Questionnaire Urinary Incontinence Short Form (ICIQ-UI SF), which provides a validated UI symptom score (range 0 - 21 points) with questions on frequency, amount and overall impact. Respondents were then contacted by telephone for an interview during which the symptom-based diagnosis of UUI or MUI was determined, and questions about alarm symptoms and UI symptoms were asked to ensure that the respondent was truly eligible for the study. Throughout the study, there was no face-to-face contact between the research group and the participants, only communication by email and telephone. The participants were randomized 1:1 to the two groups using sealed opaque envelopes prepared by an independent administrator who generated the randomization plan via the online randomization tool at http://www.randomization.com. Women randomized to the intervention group received access to the Treatment App, a smartphone app built on four themes: PFMT; bladder training; psychological education; and lifestyle information (Figure 1). The PFMT and bladder training parts of the app included 11-step and 7-step training programmes, respectively, in addition to information on pelvic floor anatomy and bladder physiology. The psychological education contained information on psychological topics related to UI, and three optional exercises. The Treatment App also offered an option to set three different times for reminder notifications, as well as an automated feedback function. In addition, the app included individual advice based on information from questionnaires and the bladder diary. The advice was generated via a pre-designed template and offered guidance to the most relevant parts of the app for each user. The control group received access to the Information App, a very limited version of the app, containing only brief information on the different topics and no training programmes or other features. Three months after randomization, the participants were asked to fill in a follow-up questionnaire and another bladder diary. In this abstract we present the results of the analysis of the primary outcome measure, the ICIQ-UI SF, measured at baseline and follow-up. Analyses of secondary outcomes, including incontinence episode frequency, are currently on-going and will be presented at a later date. Sample size calculation: Based on the findings of previous studies, improvements in the ICIQ-UI SF of 2.5 points in the Treatment App group and 0.9 points in the Information App group were assumed. To detect this difference with 80% power, 2-side test and a significance of 0.05, a sample size of 49 women was needed in each group. To allow for a dropout rate of 20%, each group needed to include 60 participants, and we therefore aimed to recruit 120 women in total. Statistical analysis: We performed Intention to Treat analysis by using a linear mixed model to estimate the difference between the groups in the ICIQ-UI SF at follow-up. A paired t-test was used for within-groups comparisons of the mean ICIQ-UI SF scores at baseline and follow-up. Results: 123 women were randomized to receive the Treatment App (n=60) or the Information App (n=63). The groups did not differ significantly in baseline measures (e.g. age, BMI, education level) nor in the mean ICIQ-UI SF scores. The mean age was 58.30 (SD 9.55) years and the mean BMI was 26.17 (SD 4.47) kg/m². The symptom-based diagnosis of MUI was more common (n=88) than that of UUI (n=35), and this distribution was equal across the two groups. The majority of women had moderate (n=73), severe (n=43) or very severe (n=4) incontinence, based on the ICIQ-UI SF scores. Two women, both in the Treatment App group, were lost to follow-up. Participants in both groups improved with regard to the mean ICIQ-UI SF score at follow-up (Treatment App group -4.67 (-5.65 to -3.69, 95% CI, p <0.001) and Information App group -1.64 (-2.31 to -0.96, 95% CI, p <0.001)). The improvement was significantly larger in the Treatment App group (p = 0.001) (Figure 2). Interpretation of results: Self-management of UUI or MUI using a mobile app led to highly significant improvements in incontinence symptoms with a significant difference compared to a control group. Thus the findings in this study show that the use of an app that includes treatment with PFMT, bladder training, psychological education and lifestyle advice was effective for women with UUI or MUI. Concluding message: Previous studies have shown that a smartphone app is an effective, easily accessible and appreciated first-line treatment option for women with SUI. The findings in the current study indicate that, provided that certain alarm symptoms or risk factors are not present, a smartphone app may be a useful addition to first-line treatment options for women with UUI or MUI who are interested in eHealth self-management.
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- Wadensten, T., et al.
(författare)
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Development and Use of an algorithm For Identifying Women With Urgency Or Mixed Urinary Incontinence Suitable For E-Health Treatment
- 2018
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Ingår i: Neurourology and Urodynamics. - : John Wiley & Sons. - 0733-2467 .- 1520-6777. ; 37:S5, s. S72-S74
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Hypothesis / aims of study One of the challenges in health care today is providing affordable care for those in need, and identifying a reasonable level of care for care-seekers. Many women with urinary incontinence might be reluctant to seek care for various reasons. Recent reviews propose lifestyle advice, pelvic floor muscle training (PFMT) and, in some cases, behavioural changes as first-line treatment for urgency (UUI) and mixed (MUI) urinary incontinence in women (1). Treatment via a smartphone app containing lifestyle advice and PFMT has been shown to be effective for, and appreciated by, women with stress urinary incontinence (SUI) (2). A smartphone app could also be a way to make treatment available to more women with UUI and MUI. The traditional recommendation of an extensive examination, on the other hand, has been described as a potential barrier to offering diagnosis and treatment to women with those conditions (3). The results of one study support the use of an algorithm combined with dipstick urinalysis for diagnosing women with urgency-predominant incontinence suitable for pharmacological treatment (3). The first aim of this study was to develop and use an extensive algorithm intended for women with UUI or MUI, to identify those with symptoms that would motivate a physical examination within usual care. The algorithm was intended for women interested in treatment via a smartphone app. To our knowledge, this is the first attempt to identify this target group in this way. The second aim was to estimate the proportion of the people interested that might be suitable for smartphone app treatment, based on the algorithm. Study design, materials and methods This report is part of a larger RCT study aimed at evaluating smartphone app treatment for women with UUI and MUI. As part of the preparations for the RCT study, a team of experienced general practitioners (GP), a Specialist Continence nurse, a urologist and a urogynecologist together developed an algorithm with questions regarding symptoms for which an examination would be judged important within usual care. The team included both researchers and clinicians. The RCT study was approved by a regional ethics board and registered in the Clinical Trials register. Recruitment was carried out via conventional methods (press releases, information to midwives, advertisements in media) as well as via Facebook advertisements. The advertisements directed interested people to the homepage of the research project, where additional information about the study and a link to a web-based screening questionnaire was provided. The screening questionnaire included questions on inclusion criteria and some background information, before presenting the questions related to the algorithm (figure 1). People who did not meet the inclusion criteria (woman, ≥18 years, ≥2 leakages/week, ≥12 month symptom duration, urgency or mixed urinary incontinence), or those who were pregnant or used another PFMT app or antimuscarinic drugs could not proceed further with the questionnaire. If a respondent gave a positive answer on any symptom from the algorithm, she was excluded and recommended to contact her normal health care provider for further assessment. Any respondent who passed the screening questionnaire in full was asked to provide her email address and thereafter received an informed consent form and a bladder diary to complete. Once these were returned, the respondent received another questionnaire and was thereafter contacted via telephone by a Specialist Continence nurse or GP. The purpose of this telephone interview was to give the diagnosis and to verify the answers to the algorithm questions. Results Following a year of meetings and discussions in the research team, a final algorithm was decided via consensus, based on previous literature on the subject as well as clinical experience. The symptoms and conditions included in the algorithm were painful urges; pyelonephritis; three or more urinary tract infections (UTI) in the last 12 months; dysuria (burning upon urination); visible haematuria; non-investigated bladder emptying difficulties; metrorrhagia; cancer in the pelvic area, bladder or bowels; decreased mobility or sensibility in the legs or pelvic area; previous stroke; neurological disease and diabetes (figure 1). The algorithm was used in the web-based screening questionnaire as described above. Out of 765 women with UUI or MUI with ≥2 leakages/week and ≥12 month duration, 523 were identified as eligible to be offered e-health treatment after exclusions. The 238 women who were excluded for symptoms in the algorithm were automatically advised to contact their normal health care provider for further assessment (figure 1). A further four women left the questionnaire before completion of all questions and were therefore not included. Of the 523 eligible women, 142 women chose to complete all the successive steps and were interviewed via telephone. In the interviews, nine women presented algorithm-related symptoms. In five cases, those symptoms were neurological (i.e. a diffuse sense of numbness in regions of the lower limbs), one woman, aged 51, also had painful urges. Another woman, aged 45, had painful urges as her only symptom. One woman, aged 64, reported having recurring visible haematuria and dysuria three months prior to the interview and had earlier been examined with cystoscopy. Another woman, aged 70, had current dysuria and was being treated for a UTI. One woman had metrorrhagia and was being investigated in usual care. All of these cases were discussed with an experienced GP and/or urogynecologist and were excluded and redirected to their normal health care provider as an extra precaution. Interpretation of results It is possible to develop an algorithm as described above via consensus within a team of experienced clinicians and researchers. Approximately two-thirds of women with UUI or MUI with ≥2 leakages/week and ≥12 month duration who are interested in an e-health intervention might be suited to this kind of treatment. An algorithm such as the one described here might be one way to identify suitable women and redirect those who should contact usual care for an assessment of specific symptoms. However, we do not know whether the respondents who were redirected to usual care had already been examined for these symptoms and/or had relevant underlying pathology. Nonetheless, our view was that the occurrence of any of the other symptoms should motivate precaution, and was a reason for the patient to contact their normal health care provider. Concluding message An algorithm such as the one described here might both help the patient (or health care personnel) to choose a reasonable level of care, and possibly also identify women who had not previously considered seeking care for certain symptoms. In the long term an algorithm might help lessen the burden of ordinary health care providers by directing interested and eligible women to suitable e-health options. We are currently evaluating the efficacy of an app treatment for women with UUI/MUI, both in the short and long term. The results will include information from registers regarding diagnosis and care for relevant conditions.
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